Abstract
Genetic algorithm is one most used evolutionary algorithm in real practice. But when genetic algorithm is used in engineering practice, the slow convergence and poor stability are the main problems. In order to overcome these problems, one new improved hybrid genetic algorithm is proposed here. In this new algorithm, the advantages of artificial immune system and traditional genetic algorithm are combined. And the basic principles in artificial immune system are introduced to improve genetic algorithm. In this new algorithm, the creation of the initial population, the mutation operation, the selection operation, and other genetic operators are all improved. At last, through the simulation experiments of some hard-optimization functions, the proposed new algorithm shows its faster convergence and better stability than a lot of existing algorithms’.
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